On a data warehouse, either manual analyses supported by appropriate visualization tools or (semi-) automatic data mining may be performed, e.g. clustering, classification and summarization. Attribute-oriented generalization is a common method for the task of summarization. Typically, in a data warehouse update operations are collected and applied to the data warehouse periodically. Then, all d...

A broad bibliographical study suggests a scarcity of quantitative models of simulation integrating both network and urban growth. This absence may be due to diverging interests of concerned disciplines, resulting in a lack of communication. We propose to proceed to an algorithmic systematic review to give quantitative elements of answer to this question. A formal iterative algorithm to retrieve...

Information Mining (also known as Knowledge Discovery Process) is a growing discipline in continuous expansion. Most of the progress accomplished, are focus on the development activities (i.e. those technical activities associated with the comprehension and adaptation of data, and the implementation of data mining algorithm). According to this conceptual framework, several process models were d...

begin{abstract} In this paper, we introduce an iterative method for amenable semigroup of non expansive mappings and infinite family of non expansive mappings in the frame work of Hilbert spaces. We prove the strong convergence of the proposed iterative algorithm to the unique solution of a variational inequality, which is the optimality condition for a minimization problem. The results present...

lsmr (least squares minimal residual) is an iterative method for the solution of the linear system of equations and leastsquares problems. this paper presents a block version of the lsmr algorithm for solving linear systems with multiple right-hand sides. the new algorithm is based on the block bidiagonalization and derived by minimizing the frobenius norm of the resid ual matrix of normal equa...

Breast cancer has become a widespread disease around the world in young women. Expert systems, developed by data mining techniques, are valuable tools in diagnosis of breast cancer and can help physicians for decision making process. This paper presents a new hybrid data mining approach to classify two groups of breast cancer patients (malignant and benign). The proposed approach, AP-AMBFA, con...

Association rule mining often requires the repeated execution of some extraction algorithm for different values of the support and confidence thresholds, as well as for different source datasets. This is an expensive process, even if we use the best existing algorithms. Hence the need for incremental mining, whereby mining results already obtained can be used to accelerate subsequent steps in t...

Introduction: Recent studies of Computed Tomography (CT) conducted on patient dose reduction have recommended using an iterative reconstruction algorithm and mA (mili-Ampere) dose modulation. The current study aimed to evaluate Iterative Dose Reduction Algorithm (IDREAM) as an iterative reconstruction algorithm. Material and Methods: Two CT p...

in this paper, downlink resource allocation for a sparse code multiple access (scma) based heterogeneous  cellular networks (hcn) is investigated. the main aim of this paper is to obtain joint power allocation and codebook assignment to achieve the least total system transmit power. in this regard, the proposed objective function is formulated as total transmit power subject to users minimum ra...